FDE as a service
A forward deployed engineer is a hybrid profile: someone who understands the business problem, builds or adapts the solution, integrates it into the tools your teams already use, and stays long enough for the adoption to hold. Large software companies employ these people because they discovered that the distance between a capable model and a changed workflow is not a product gap but a deployment gap, and that nobody outside the company could close it on their behalf. Most organisations buying AI have the same gap and no reason to build a permanent team around it. This service is that role, engaged for one project rather than hired: the same work, the same deliverables, and an explicit obligation to leave your team able to run what was built without us.
What the role actually covers
Four things, in order, and the order matters because skipping the first is how most projects end up delivering something correct that nobody wanted.
Understanding the business problem. Not gathering requirements. Establishing what is actually wrong, which is usually adjacent to what was described, by looking at how the work is done today rather than at how it is supposed to be done. This phase ends with a statement of the problem you recognise and that contains something you had not said out loud.
Building or adapting the solution. Real engineering against your data and your constraints: connectors, retrieval, evaluation against cases your own experts labelled, and error handling designed so the system fails visibly rather than confidently.
Integrating it into your tools. The part that decides whether it is used. A system that lives in its own interface competes for attention with everything else your teams have open. One that appears inside the tool they already have does not.
Supporting adoption. Sitting with the people whose work changes, watching them not use it, and finding out why. This is the stage most engagements skip and the stage that determines whether the previous three were worth paying for.
What we do not do
We do not sell software, we do not resell anybody else's platform, and we take no commission on any tool we recommend. This matters because the advice on which model or which vendor to use is worth very little from someone who is paid differently depending on the answer.
We do not write strategy documents. There is a real place for AI strategy work and it is not this: the deliverable here is a system that runs in your environment, and the thinking that goes into it is expressed as decisions rather than as slides.
We do not take over. A deployment where nobody from your organisation touched the system is a deployment that decays as soon as we stop, and we have no interest in producing that outcome even though it is the one that most reliably generates a second engagement.
What you get, concretely
A running system in your environment, which you own outright including the code. A written account of what your data actually contains as opposed to what it is documented to contain, which is frequently the most reused artefact. An evaluation set built from your own cases and labelled by your own experts, which outlives whatever model you happen to be using today. And a handover, meaning at least one person inside your organisation who has worked on the system with us and can change it.
You also get the answer to a question you may not have asked: which parts of this problem are not worth solving with software. That answer arrives early, it usually removes something from the scope, and it is the part of the engagement that most often pays for itself.
How an engagement is shaped
The first phase is short and deliberately cheap: enough time to establish what is actually wrong and what the realistic ceiling is. It ends with a written recommendation, and a meaningful minority of projects end there, because the honest recommendation is not to build. That is a legitimate outcome and it is priced accordingly.
If it goes ahead, the build phase runs against a defined problem with a named internal owner and agreed access to data, which is the single largest predictor of whether a deployment finishes on time. We will ask about access before we quote, and if the answer is that a credential takes eleven weeks, that is not a reason not to proceed but it is a reason for the timeline to say so honestly.
The engagement ends with the handover, which is a deliverable rather than an event. It includes the documentation, the evaluation set, and a period where your own person runs the system and we answer questions rather than the other way round.
When this is the wrong thing to buy
If you have a strong internal team and the problem is well understood, you do not need this and should build it yourselves; we will tell you so in the first conversation. If the real obstacle is organisational rather than technical, a deployment engineer will not fix it and the money is better spent elsewhere. And if nobody senior actually wants the change, no amount of good engineering survives contact with that, which is the most expensive lesson available in this field and the one we would rather you did not pay for.
Talk to us about one specific problem
Bring a problem rather than a brief. Thirty minutes is usually enough to tell whether it is a deployment problem, an organisational one, or one you should not be solving with software at all.
A first conversation is thirty minutes and is not a sales call. If the answer is that you do not need us, that is a useful outcome and we will say so.
